TY - CHAP
T1 - Geospatial and Temporal Semantic Analytics
Y1 - 2007
A1 - Matthew Perry
A1 - Ismailcem Budak Arpinar
A1 - Amit Sheth
A1 - Farshad Hakimpour
KW - Ontology
KW - rdf
KW - Semantic Analytics
KW - Semantic Association
KW - Spatiotemporal Thematic Context
AB - The amount of digital data available to researchers and knowledge workers has grown tremendously in recent years. This is especially true in the geography domain. As the amount of data grows, problems of data relevance and information overload become more severe. The use of semantics has been proposed to combat these problems (Berners-Lee et al., 2001; Egenhofer,
ER -
TY - CHAP
T1 - Spatiotemporal-Thematic Data Processing in Semantic Web
Y1 - 2007
A1 - Matthew Perry
A1 - Amit Sheth
A1 - Farshad Hakimpour
A1 - Boanerges Aleman-Meza
KW - Event
KW - GIS
KW - rdf
KW - Semantics
KW - Spatiotemporal
KW - spatiotemporal thematic (STT) functions and proximity
AB - This chapter presents practical approaches to data processing in space, time and theme dimensions using current Semantic Web technologies. It describes how we obtain geographic and even data from Internet sources and also how we integrate then into an RDF store. We briefly introduce a set of functionalities in space, time and semantics. These functionalities are implemented based on our existing technology for main-memory based RDF data processing developed at the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client side applications that are developed using a combination of our services with Google maps service.
ER -
TY - CONF
T1 - Supporting Complex Thematic, Spatial and Temporal Queries over Semantic Web Data
T2 - 2nd International Conference on Geospatial Semantics (GEOS 07)
Y1 - 2007
A1 - Amit Sheth
A1 - Prateek Jain
A1 - Farshad Hakimpour
A1 - Matthew Perry
AB - Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. Often, the analytical process requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities. We discuss modeling issues and present a set of semantic query operators. We also describe an efficient implementation in Oracle DBMS and demonstrate the scalability of our approach with a performance study using a large synthetic dataset from the national security domain.
JA - 2nd International Conference on Geospatial Semantics (GEOS 07)
PB - GeoS 2007: http://geosco.org/geos2007/
CY - Mexico City, MX
ER -
TY - Generic
T1 - SwetoDblp Ontology of Computer Science Publications
Y1 - 2007
A1 - Amit Sheth
A1 - Farshad Hakimpour
A1 - Boanerges Aleman-Meza
A1 - Ismailcem Budak Arpinar
KW - Ontology
KW - Ontology Population
KW - Semantic Analytics
KW - XML
AB - SwetoDblp is a large populated ontology with a shallow schema yet a large number of real- world instance data. We describe how such ontology is built from an XML source and how it can be maintained. Instead of a one-to-one mapping from XML to RDF, the creation of the ontology emphasizes the addition of relationships and the value of URIs. SwetoDblp is publicly available online. We also summarize research efforts that have used or are using this freely available community resource.
PB - Web Semantics: Science, Services and Agents on the World Wide Web
ER -
TY - CONF
T1 - Visualization of Events in a Spatially and Multimedia Enriched Virtual Environment
T2 - IEEE Intelligence and Security Informatics (ISI)
Y1 - 2007
A1 - Farshad Hakimpour
A1 - Leonidas Deligiannidis
A1 - Amit Sheth
AB - Semantic Event Tracker (SET) is a highly interactive visualization tool for tracking and associating activities (events) in a spatially and Multimedia Enriched Virtual Environment. SET provides integrated views of information spaces while providing overview and detail to improve perception and evaluation of complex scenarios. We model an event as an object that describes an action and its location, time, and relations to other objects. Real world event information is extracted from Internet sources, then stored and processed using Semantic Web technologies that enable us to discover semantic associations between events. We use RDF graphs to represent semantic metadata and ontologies. SET is capable of visualizing as well as navigating through the event data in all three aspects of space, time and theme.
JA - IEEE Intelligence and Security Informatics (ISI)
CY - New Brunswick, NJ
ER -
TY - ABST
T1 - What, Where and When: Supporting Semantic, Spatial and Temporal Queries in a DBMS
Y1 - 2007
A1 - Prateek Jain
A1 - Matthew Perry
A1 - Amit Sheth
A1 - Farshad Hakimpour
KW - RDF and Ontology and Semantic Analytics and SPARQL
AB - Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. The outcome of the analytical process in these applications often hinges on uncovering and analyzing complex relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful in these applications. However, these analysis mechanisms are primarily intended for thematic relationships. We describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities and describe an efficient implementation in Oracle DBMS. Additionally, we demonstrate the scalability of our approach with a performance study using a synthetic dataset from the national security domain.
ER -
TY - CONF
T1 - Analyzing Theme, Space and Time: An Ontology-based Approach
T2 - Proc. ACM International Symposium on Geographic Information Systems
Y1 - 2006
A1 - Matthew Perry
A1 - Farshad Hakimpour
A1 - Amit Sheth
AB - The W3C's Semantic Web Activity is illustrating the use of semantics for information integration, search, and analysis. However, the majority of the work in this community has focused more on the thematic aspects of information and has paid less attention to its spatial and temporal dimensions. In this paper, we present an integrative ontology-based framework incorporating the thematic, spatial, and temporal dimensions of information. This framework is built around the RDF metadata model. Our ultimate goal is to provide an information system which allows searching and analysis of relationships in any or all of the three dimensions of space, time, and theme. Toward this end, we present an upper-level ontology combining concepts and relationships from both the thematic and spatial dimensions and show how to incorporate temporal semantics into this ontology. We also introduce the notion of a thematic context linking entities of differing dimensions and define a set of query operators built upon these contexts.
JA - Proc. ACM International Symposium on Geographic Information Systems
CY - Arlington, VA
ER -
TY - CONF
T1 - Analyzing Theme, Space and Time: An Ontology-based Approach
T2 - Analyzing Theme, Space and Time: An Ontology-based Approach
Y1 - 2006
A1 - Matthew Perry
A1 - Farshad Hakimpour
A1 - Amit Sheth
AB - The W3C's Semantic Web Activity is illustrating the use of semantics for information integration, search, and analysis. However, the majority of the work in this community has focused more on the thematic aspects of information and has paid less attention to its spatial and temporal dimensions. In this paper, we present an integrative ontology-based framework incorporating the thematic, spatial, and temporal dimensions of information. This framework is built around the RDF metadata model. Our ultimate goal is to provide an information system which allows searching and analysis of relationships in any or all of the three dimensions of space, time, and theme. Toward this end, we present an upper-level ontology combining concepts and relationships from both the thematic and spatial dimensions and show how to incorporate temporal semantics into this ontology. We also introduce the notion of a thematic context linking entities of differing dimensions and define a set of query operators built upon these contexts.
JA - Analyzing Theme, Space and Time: An Ontology-based Approach
ER -
TY - CONF
T1 - Analyzing Theme, Space and Time: An Ontology-based Approach (poster)
T2 - 5th International Semantic Web Conference
Y1 - 2006
A1 - Matthew Perry
A1 - Farshad Hakimpour
A1 - Amit Sheth
KW - RDF and Ontology and Spatial Ontology and Spatial Relationships and Domain Ontology and Temporal Relationships and Temporal Ontology and Spatio-temporal-thematic Querying and Data Modeling
JA - 5th International Semantic Web Conference
PB - 5th International Semantic Web Conference
CY - Athens, GA
ER -
TY - CONF
T1 - Data Processing in Space, Time, and Semantics Dimensions
T2 - Data Processing in Space, Time, and Semantics Dimensions
Y1 - 2006
A1 - F. Hakimpour
A1 - Boanerges Aleman-Meza
A1 - M. Perry
A1 - Amit Sheth
AB - This work presents an experimental system for data processing in space, time and semantics dimensions using current Semantic Web technologies. The paper describes how we obtain geographic and event data from Internet sources and also how we integrate them into an RDF store. We briefly introduce a set of functionalities in space, time and semantics dimensions. These functionalities are implemented based on our existing technology for main-memory based RDF data processing developed in the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client side applications that are developed using a combination of our services with Google map service.
JA - Data Processing in Space, Time, and Semantics Dimensions
ER -
TY - CONF
T1 - Semantic WS-Agreement Partner Selection
T2 - Semantic WS-Agreement Partner Selection
Y1 - 2006
A1 - Nicole Oldham
A1 - Kunal Verma
A1 - Amit Sheth
A1 - Farshad Hakimpour
AB - In a dynamic service oriented environment it is desirable for service consumers and providers to offer and obtain guarantees regarding their capabilities and requirements. WS-Agreement defines a language and protocol for establishing agreements between two parties. The agreements are complex and expressive to the extent that the manual matching of these agreements would be expensive both in time and resources. It is essential to develop a method for matching agreements automatically. This work presents the framework and implementation of an innovative tool for the matching providers and consumers based on WS-Agreements. The approach utilizes Semantic Web technologies to achieve rich and accurate matches. A key feature is the novel and flexible approach for achieving user personalized matches.
JA - Semantic WS-Agreement Partner Selection
CY - New York, NY
ER -